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Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma
Michele Ceccarelli, Floris P Barthel, Tathiane M. Malta, Thaís S. Sabedot, Sofie R. Salama, Bradley A. Murray, Olena Morozova, Yulia Newton, Amie Radenbaugh, Stefano Maria Pagnotta, Samreen Anjum, Jiguang Wang, Ganiraju C. Manyam, Pietro Zoppoli, Shiyun Ling, Arjun A. Rao, Mia Grifford, Andrew D. Cherniack, Hailei Zhang, Laila Poisson, Carlos Gilberto Carlotti, Daniela Pretti da Cunha Tirapelli, Arvind Rao, Tom Mikkelsen, Ching C. Lau, W. K. Alfred Yung, Raúl Rabadán, Jason T. Huse, Daniel J. Brat, Norman L. Lehman, Jill S. Barnholtz‐Sloan, Siyuan Zheng, Kenneth R. Hess, Ganesh Rao, Matthew Meyerson, Rameen Beroukhim, Lee Cooper, Rehan Akbani, Margaret Wrensch, David Haussler, Kenneth D. Aldape, Peter W. Laird, David H. Gutmann, Houtan Noushmehr, Antonio Iavarone, Roel G.W. Verhaak, Harindra Arachchi, J. Todd Auman, Miruna Balasundaram, Saianand Balu, Gene H. Barnett, Stephen Baylin, Sue Bell, Christopher C. Benz, Natalie Bir, Keith L. Black, Tom Bodenheimer, Lori Boice, Jay Bowen, Christopher A. Bristow, Yaron S.N. Butterfield, Qingrong Chen, Lynda Chin, Juok Cho, Eric Chuah, Sudha Chudamani, Simon G. Coetzee, Mark L. Cohen, Howard Colman, Marta Couce, Fulvio D’Angelo, Tanja M. Davidsen, Amy Davis, John A. Demchok, Karen Devine, Li Ding, Rebecca Duell, J. Bradley Elder, Jennifer Eschbacher, Ashley Fehrenbach, Martin L. Ferguson, Scott Frazer, Gregory N. Fuller, Jordonna Fulop, Stacey Gabriel, Luciano Garofano, Julie M. Gastier-Foster, Nils Gehlenborg, Mark Gerken, Gad Getz, Caterina Giannini, William J. Gibson, Angela Hadjipanayis, D. Neil Hayes, David I. Heiman, Beth Hermes, Joe Hilty, Katherine A. Hoadley, Alan P. Hoyle, Mei Huang, Corbin D. Jones, Steven J.M. Jones, Zhenlin Ju, Alison Kastl, Ady Kendler, Jaegil Kim, Raju Kucherlapati, Phillip H. Lai, Michael S. Lawrence, Semin Lee, Kristen Leraas, Tara M. Lichtenberg, Pei Lin, Yuexin Liu, Jia Liu, Julia Y. Ljubimova, Yiling Lu, Yussanne Ma, Dennis T. Maglinte, Harshad S. Mahadeshwar, Marco A. Marra, Mary McGraw, Christopher McPherson, Shaowu Meng, Piotr A. Mieczkowski, C. Ryan Miller, Gordon B. Mills, Richard A. Moore, Lisle E. Mose, Andrew J. Mungall, Rashi Naresh, Theresa Naska, Luciano Neder, Michael S. Noble, Ardene Noss, Brian Patrick O’Neill, Quinn T. Ostrom, Cheryl A. Palmer, Angeliki Pantazi, Michael Parfenov, Peter J. Park, Joel S. Parker, Charles M. Perou, Christopher R. Pierson, Todd Pihl, Alexei Protopopov, Nilsa C. Ramirez, W. Kimryn Rathmell, Xiaojia Ren, Jeffrey Roach, A. Gordon Robertson, Gordon Saksena, Jacqueline E. Schein, Steven E. Schumacher, Jonathan G. Seidman, Kelly Senecal, Sahil Seth, Hui Shen, Yan Shi, Juliann Shih, Kristen Shimmel, Hugues Sicotte, Suzanne Sifri, Tiago C. Silva, Janae V. Simons, Rosy Singh, Tara Skelly, Andrew E. Sloan, Heidi J. Sofia, Matthew G. Soloway, Xingzhi Song, Carrie Sougnez, Camila Souza, Susan M. Staugaitis, Huandong Sun, Charlie Sun, Donghui Tan, Jiabin Tang, Yufang Tang, Leigh B. Thorne, Felipe Amstalden Trevisan, Timothy J. Triche, David Van Den Berg, Umadevi Veluvolu, Doug Voet, Yunhu Wan, Zhining Wang, Ronald E. Warnick, John N. Weinstein, Daniel J. Weisenberger, Matthew D. Wilkerson, Lisa Wise, Yingli Wolinsky, Junyuan Wu, Andrew Wei Xu, Lixing Yang, Liming Yang, Travis Zack, Jean C. Zenklusen, Jianhua Zhang, Wei Zhang, Jiashan Zhang, Erik Zmuda
Bibliographic record
VenueCell · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesNational Institutes of HealthNational Cancer InstituteNational Human Genome Research InstituteFundação de Amparo à Pesquisa do Estado de São PauloCancer Prevention and Research Institute of Texas
KeywordsBiologyGliomaATRXPilocytic astrocytomaDNA methylationAstrocytomaTelomereGeneticsGeneCancer researchMutationGene expression
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.017
GPT teacher head0.268
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations2,338
Published2016
Admission routes1
Has abstractno